1. Field of the Invention
The present invention relates to a technology for aligning, among a plurality of medical images, image data on a tissue to be objected to be an object of diagnosis and observation, including such organs as a heart, liver, pancreas, kidney, spleen, brain and lung, or such biotissue as a tumor (coordinating, among the images, each image point corresponding to each portion of a tissue to be objected in each image), and more particularly to a medical image data alignment apparatus, method and program for aligning different kinds of image data on a tissue to be objected, between a medical image obtained by an image diagnostic apparatus (hereafter called “first kind image diagnostic apparatus”) capable of generating an image of anatomical form information on the tissue to be objected, such as an X-ray CT (Computed Tomography) apparatus and MRI (Magnetic Resonance Imaging) apparatus and a medical image obtained by an image diagnostic apparatus (hereafter called “second kind image diagnostic apparatus”) capable of generating an image of function information including blood flow, for example, in a tissue to be objected, such as a SPECT (Single-Photon Emission Computed Tomography) apparatus.
2. Description of the Prior Art
Photographing a tissue to be objected using a CT apparatus and an MRI apparatus (first kind image diagnostic apparatus), which can generate an image of an anatomical form information on the tissue to be objected without involving a surgical procedure, is widely used in clinical fields in order to detect a structural alteration, functional disorder and presence of a pathologically altered portion of a tissue to be objected.
In particular, the image diagnosis by the X-ray CT apparatus, of which performance has advanced recently, exhibits high performance in detecting blood vessels responsible for supplying nutrition to cardiac muscles in an ischemic state (mainly coronary arteries which cause stricture by arteriosclerosis and plaque), which is critical for diagnosing ischemic heart diseases represented by cardiac infarction, is receiving attention as a method which has little effect on and imposes little stress on a patient. However a stricture of coronary artery does not always cause immediate ischemia, so diagnosis by CT image alone increases the number of false positives.
To solve this problem, a method for using the SPECT image obtained by a SPECT apparatus (second kind image diagnostic apparatus) which can generate an image of function information, such as blood flow, in addition to a CT image, so as to use an integrated image of these two medical images for diagnosis, is drawing attention. According to a diagnosis based on this integrated image, major improvements can be made in decreasing the number of false positives, compared with diagnosis based on a CT image alone (see Non-patent Document 1 listed below).
Generally in the case of integrating different kinds of medical images, such as a CT image and a SPECT image, these respective image data must be aligned, and this alignment is often manually performed by a specialist or the like. However the information to be generated into an image is different and therefore correlation is low between a CT image and a SPECT image, and the resolution of the SPECT image is low, so even if the physician has extensive experience in image diagnosis, it takes a long time to perform alignment with sufficient accuracy and reproducibility.
Therefore various methods for automatically aligning each image data of different kinds of medical images using a computer have been proposed (see Non-Patent Documents 2 and 3 listed below, and Japanese Patent Application Laid-open No. H10-137231).
According to the method in Non-patent Document 2, the left ventricle of a heart in an MR image obtained by an MRI apparatus is segmented by a threshold base method, and the left ventricle of the segmented MR image and a SPECT image are automatically aligned using a mutual information amount and a rigid transformation (rigid registration).
According to the method in Non-patent Document 3, a left ventricle model is constructed by segmenting a left ventricle in a CT image obtained by a CT apparatus, and this left ventricle model and SPECT image are automatically aligned by each method of the rigid transformation and non-rigid transformation (non-rigid registration), and also is manually aligned to verify the accuracy of the automatic alignment.
According to the method in Japanese Patent Application Laid-open No. H10-137231, image data on a brain in a CT image and image data on the brain in a SPECT image are aligned based on a conformity of the surface form of a skull in the CT image and the surface form of the skull in the SPECT image.
[Non-Patent Document 1]
Shmuel Rispler, Zohar Keidar, Eduard Ghersin, Ariel Roguin, Adrian Soil, Robert Dragu, Diana Litmanavich, Alex Frenkel, Doran Aronson, Ahuva Engel, Rafael Beyar and Ora Israel: “Integrated Single-Photon Emission Computed Tomography and Computed Tomography Coronary Angiography for the Assessment of Hemodynamically Significant Coronary Artery Lesions,” Journal of the American College of Cardiology, Vol. 49, No. 10, pp. 1059-1067, 2007
[Non-Patent Document 2]
Usaf E. Alsdl, Gilbert A. Hurwitz, Damini Dey, David Levin, Maria Dragova and Piotr J. Slomka: “Automated Image Registration of Gated Cardiac Single-Photon Emission Computed Tomography and Magnetic Resonance Imaging,” Journal of Magnetic Resonance Imaging, Vol. 19, No. 3, pp. 283-290, 2004
[Non-Patent Document 3]
Hidenobu Nakajo, Shin-ichiro Kumita, Keiichi Cho, and Tatsuo Kumazaki: “Three-dimensional registration of myocardial perfusion SPECT and CT coronary angiography”, Annals of Nuclear Medicine, Vol. 19, No. 3, pp. 207-215, 2005
The methods according to the Non-patent Documents 2 and 3 mentioned above perform stable alignment by extracting the left ventricle portion, of which correlation with the SPECT image is relatively high, from the CT image or MRI image, and using this portion for alignment, but alignment accuracy greatly depends on the result of segmenting the left ventricle, so a problem is that the alignment accuracy falls considerably unless a good segmentation result is obtained.
The method according to Japanese Patent Application Laid-open No. H10-137231 mentioned above, on the other hand, must extract some anatomical form information from the SPECT image of which resolution is low, so this method is effective if an area of which form information can be extracted relatively easily, like the case of a skull, is imaged, but the problem is that it takes an enormous amount of time to extract the form information from the SPECT image if such an appropriate area does not exist.